Systems and methods for generating calm or quiet routes

ABSTRACT

Systems and methods for generating calm or quiet routes are provided. When a user requests navigation directions and indicates a preference for a calm route, a plurality of routes between the origin location and the destination location requested by the user may be identified. Historical sensor data (e.g., including heart rate data, exterior vehicle noise level data, accelerometer data) and traffic data associated with route segments of each of the routes may be analyzed to identify indications of calmness associated with each route segment. Current traffic data associated with the route segments may be analyzed to assign a traffic score representing a level of congestion along the segment and corresponding to a level of insurance risk associated with traversing the segment. Based at least in part upon the indications of calmness and the traffic score associated with each route segment, a route may be selected and presented to the user.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to vehicle safety and, moreparticularly, to systems and methods for generating calm or quietroutes.

BACKGROUND

The background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent it is described in thebackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing, are neitherexpressly nor impliedly admitted as prior art against the presentdisclosure.

While current navigation applications may generate vehicle routes thatprovide the fastest or shortest drive between an origin location and adestination location, current navigation applications typically do notaccount for driver stress level when generating a route. However,certain vehicle routes may be particularly stressful for some drivers.For example, certain routes, such as, e.g., loud routes, congestedroutes, routes with large numbers of lanes, routes including uneventerrain, etc., may be stressful for certain drivers. However, as adriver's stress level rises, he or she may be more likely to get into avehicle accident.

SUMMARY

In one aspect, a computer-implemented method of generating a calm routeis provided. The method comprises: receiving, by one or more processors,a user request for navigation directions from an origin location to adestination location, wherein the user request includes an indication ofa user preference for a calm route; identifying, by one or moreprocessors, based at least in part upon map data, a plurality of routesbetween the origin location and the destination location; analyzing, byone or more processors, historical sensor data associated with routesegments of each of the plurality of routes between the origin locationand the destination location to identify indications of calmnessassociated with each route segment, wherein the historical sensor datais received from at least a heart rate sensor, a microphone fixed to avehicle and configured to receive noise data from an exterior of thevehicle, an accelerometer, and an external traffic database; wherein thehistorical sensor data associated with each route segment includes: 1)heart rate data associated with operators of vehicles captured whiledriving the route segment, 2) noise data received from exteriors ofvehicles traveling along the route segment, 3) accelerometer dataindicative of hard breaking and acceleration events captured along theroute segment, and 4) historical traffic data along the route segment;assigning, by one or more processors, a score to current traffic dataassociated with the route segments of each of the plurality of routesbetween the origin location and the destination location to represent alevel of congestion along the segment, where the score corresponds to alevel of insurance risk associated with traversing the segment;selecting, by one or more processors, one of the plurality of routesbetween the origin location and the destination location based at leastin part upon the indications of calmness associated with the routesegments of the route and the score assigned to the current trafficdata; and presenting, by one or more processors, the selected route fromthe origin location to the destination location to a user.

In another aspect, a computer system for generating a calm route,comprising: one or more processors; and a non-transitory program memorycommunicatively coupled to the one or more processors and storingexecutable instructions. The executable instructions, when executed bythe one or more processors, cause the computer system to: receive a userrequest for navigation directions from an origin location to adestination location, wherein the user request includes an indication ofa user preference for a calm route; identify, based at least in partupon map data, a plurality of routes between the origin location and thedestination location; analyze historical sensor data associated withroute segments of each of the plurality of routes between the originlocation and the destination location to identify indications ofcalmness associated with each route segment, wherein the historicalsensor data is received from at least a heart rate sensor, a microphonefixed to a vehicle and configured to receive noise data from an exteriorof the vehicle, an accelerometer, and an external traffic database;wherein the historical sensor data associated with each route segmentincludes: 1) heart rate data associated with operators of vehiclescaptured while driving the route segment, 2) noise data received fromexteriors of vehicles traveling along the route segment, 3)accelerometer data indicative of hard breaking and acceleration eventscaptured along the route segment, and 4) historical traffic data alongthe route segment; assign a score to current traffic data associatedwith the route segments of each of the plurality of routes between theorigin location and the destination location to represent a level ofcongestion along the segment, where the score corresponds to a level ofinsurance risk associated with traversing the segment; select one of theplurality of routes between the origin location and the destinationlocation based at least in part upon the indications of calmnessassociated with the route segments of the route and the score assignedto the current traffic data; and present the selected route from theorigin location to the destination location to a user.

In still another aspect, a tangible, non-transitory computer-readablemedium for generating a calm route is provided. The tangible,non-transitory computer-readable medium stores executable instructionsthat, when executed by at least one processor of a computer system,cause the processor to: receive a user request for navigation directionsfrom an origin location to a destination location, wherein the userrequest includes an indication of a user preference for a calm route;identify, based at least in part upon map data, a plurality of routesbetween the origin location and the destination location; analyzehistorical sensor data associated with route segments of each of theplurality of routes between the origin location and the destinationlocation to identify indications of calmness associated with each routesegment, wherein the historical sensor data is received from at least aheart rate sensor, a microphone fixed to a vehicle and configured toreceive noise data from an exterior of the vehicle, an accelerometer,and an external traffic database; wherein the historical sensor dataassociated with each route segment includes: 1) heart rate dataassociated with operators of vehicles captured while driving the routesegment, 2) noise data received from exteriors of vehicles travelingalong the route segment, 3) accelerometer data indicative of hardbreaking and acceleration events captured along the route segment, and4) historical traffic data along the route segment; assign a score tocurrent traffic data associated with the route segments of each of theplurality of routes between the origin location and the destinationlocation to represent a level of congestion along the segment, where thescore corresponds to a level of insurance risk associated withtraversing the segment; select one of the plurality of routes betweenthe origin location and the destination location based at least in partupon the indications of calmness associated with the route segments ofthe route and the score assigned to the current traffic data; andpresent the selected route from the origin location to the destinationlocation to a user.

Depending upon the embodiment, one or more benefits may be achieved.These benefits and various additional objects, features and advantagesof the present disclosure can be fully appreciated with reference to thedetailed description and accompanying drawings that follow.

BRIEF DESCRIPTION OF THE DRAWINGS

The figures described below depict various aspects of the systems andmethods disclosed herein. Advantages will become more apparent to thoseskilled in the art from the following description of the embodimentswhich have been shown and described by way of illustration. As will berealized, the present embodiments may be capable of other and differentembodiments, and their details are capable of modification in variousrespects. Accordingly, the drawings and description are to be regardedas illustrative in nature and not as restrictive.

FIG. 1 illustrates a block diagram of an exemplary system for generatingcalm or quiet routes, in accordance with some embodiments.

FIG. 2A illustrates an exemplary user interface display, in accordancewith some embodiments.

FIG. 2B illustrates an exemplary user interface display, in accordancewith some embodiments.

FIG. 3 illustrates a flow diagram of an exemplary method for generatingcalm or quiet routes, in accordance with some embodiments.

DETAILED DESCRIPTION

As discussed above, while current navigation applications may generatevehicle routes that provide the fastest or shortest drive between anorigin location and a destination location, current navigationapplications typically do not account for driver stress level whengenerating a route. However, certain vehicle routes may be particularlystressful for some drivers. For example, certain routes, such as, e.g.,loud routes, congested routes, routes with large numbers of lanes,routes including uneven terrain, etc., may be stressful for certaindrivers. However, as a driver's stress level rises, he or she may bemore likely to get into a vehicle accident.

The present application provides systems and methods for generating calmor quiet routes. When a driver indicates that he or she wishes to take acalm or quiet route from an origin location to a destination location, amobile device application may generate a calm or quiet route byanalyzing sensor data associated with historical routes or routesegments driven by a particular driver or by a driver population todetermine and/or predict which routes or route segments will beassociated with calm drivers and/or quiet routes. For example, softer orless frequent braking, fewer accelerations, more consistent velocity,less speeding, and less honking may be associated with calmer driving.Moreover, sensor data indicative of quiet vehicle interior orsurroundings, or indicative of nature sounds (e.g., birds, ocean waves,crickets) may be associated with calmer driving. Additionally, a lowerdriver heart rate (e.g., as determined by a wearable fitness tracker)may be associated with calmer driving. Furthermore, routes with fewerlanes and/or less congestion or less construction may be associated withcalmer driving. Advantageously, the systems and methods provided by thepresent application provide calmer or quieter routes for drivers, whichmay reduce stress levels for drivers and decrease the risk of vehicleaccidents.

FIG. 1 illustrates a block diagram of an exemplary system 100 forgenerating calm or quiet routes, in accordance with some embodiments.The high-level architecture illustrated in FIG. 1 may include bothhardware and software applications, as well as various datacommunications channels for communicating data between the varioushardware and software components, as is described below. The system 100may include one or more onboard computing devices 102, which may each bepositioned within or otherwise associated with a respective vehicle 104(which may be, e.g., a car, a truck, a boat, a motorcycle, a motorizedscooter, or any other vehicle). For instance, an onboard computingdevice 102 may be built into the vehicle 104, or may be a mobile device(such as, e.g., a smart phone, a smart watch, a GPS system, etc.)associated with a driver or operator of the vehicle 104.

Each onboard computing device 102 may communicate with various sensorsto receive sensor data captured as the respective vehicles 104 travelalong various routes. This sensor data may include sensor data capturedby onboard sensors associated with the vehicle, such as a microphone 106configured to capture noise data from an exterior of the vehicle 104.Additionally, the onboard computing devices 102 may communicate withsensor devices associated with a driver or operator of the vehicle 104,such as, e.g., a heart rate monitor 108 (e.g., a dedicated heart ratemonitor worn by the driver or operator, or a smart watch or wearablefitness tracker worn by the driver or operator) configured to captureheart rate data associated with the driver or operator of the vehicle104. Furthermore, the onboard computing devices 102 may include motionsensors 110 such as accelerometers or gyroscopes configure to captureinstances of acceleration and/or instances of hard braking, and/orlocation sensors 112 such as global positioning sensors configured tocapture location data, or may communicate with external accelerometersand/or location sensors positioned within the vehicle 104.

Furthermore, each onboard computing device 102 may include one or moreprocessors 114, such as one or more microprocessors, controllers, and/orany other suitable type of processors, and a memory 116 (e.g., volatilememory, non-volatile memory) accessible by the respective one or moreprocessors 114, (e.g., via a memory controller). The one or moreprocessors 114 may interact with the memory 116 to obtain, for example,computer-readable instructions stored in the memory 116. In particular,the computer-readable instructions stored on the memory 116 may includeinstructions for executing a navigation application 118 configured togenerate and display navigation directions for a calm route for a userof the onboard computing device 102. Moreover, the computer-readableinstructions stored on the memory 116 may include instructions forcarrying out one or more of the steps of the method 300 described ingreater detail below with respect to FIG. 3.

Furthermore, each onboard computing device 102 may include a userinterface 120, which may be configured to receive input from users(e.g., requests for navigation directions, indications of preferencesfor calm or quiet routes, etc.) and/or to display information to users(e.g., navigation directions generated by the navigation application118).

Each onboard computing device 102 may be configured to communicate witha server 122, e.g., via a network 124. For instance, each onboardcomputing device 102 may communicate data captured by sensors such asthe microphone 106, the heart rate monitor 108, the motion sensor 110,the location sensor 112, etc., to the server 122. In some examples, theserver 122 may be configured to store the sensor data from each of theonboard computing devices 102 associated with various respectivevehicles 104 in a historical sensor database 125. Furthermore, eachonboard computing device 102 may communicate user input received via theuser interface 120, such as requests for navigation directions,indications of preferences for calm or quiet routes, etc., to the server122.

The server 122 may include one or more processors 126, such as one ormore microprocessors, controllers, and/or any other suitable type ofprocessors, and a memory 128 (e.g., volatile memory, non-volatilememory) accessible by the respective one or more processors 126, (e.g.,via a memory controller). The one or more processors 126 may interactwith the memory 128 to obtain, for example, computer-readableinstructions stored in the memory 128. In particular, thecomputer-readable instructions stored on the memory 126 may includeinstructions for executing various applications, such as, e.g., acalm/quiet route segment identifier 130, a traffic score generator 132,and a route generator 134. As the processors 126 execute theapplications, the server 122 may access various databases, which may beinternal or external, such as the historical sensor database 125configured to store historical sensor data captured by the onboardcomputing devices 102 (and/or from other sources), a traffic database136 storing historical and/or current traffic data associated withvarious routes and/or route segments, a map database 138 storing mapdata indicating various routes and/or route segments as well aslocations associated with various addresses, weather databases (notshown), etc.

The calm/quiet route segment identifier 130 may be configured to analyzevarious route segments in order to identify indications of calmnessassociated with each route segment. In particular, the calm/quiet routesegment identifier 130 may analyze historical sensor data from thehistorical sensor data database 125 in order to identify indications ofcalmness associated with each route segment. For example, the calm/quietroute segment identifier 130 may correlate historical location datacaptured at each vehicle at various times with historical noise data,heart rate data, and acceleration and/or gyroscope data captured at thesame times to determine locations associated with each noise data point,each heart rate data point, and each acceleration and/or gyroscope datapoint. In particular, the calm/quiet route segment identifier 130 maydetermine which locations correspond to sensor data associated with calmdriving. For example, the calm/quiet route segment identifier 130 mayidentify locations in which the historical noise data indicates averageexterior volumes below a certain threshold value, and/or locations inwhich the historical noise data indicates audible exterior noisesassociated with natural environments, indicating that route segmentsincluding those locations generally include fewer human-generatednoises, such as vehicle honking, yelling, construction noises, etc., andare consequently more calm. As another example, the calm/quiet routesegment identifier 130 may identify locations in which the historicalheart rate data indicates an average operator heart rate below apredetermined heart rate threshold, indicating that drivers drivingroute segments including those locations are typically calm.Furthermore, as still another example, the calm/quiet route segmentidentifier 130 may identify locations in which the historicalaccelerometer and/or gyroscope data indicates an average number of hardbreaking and/or acceleration events that is below a certain thresholdvalue, indicating that route segments including these locationstypically include fewer stops, and accordingly may be associated withmore calm driving.

In some examples, the calm/quiet route segment identifier 130 mayanalyze historical traffic data (e.g., from the traffic database 136) inorder to identify indications of calmness associated with each routesegment. For instance, historical traffic data indicating a historicallevel of congestion below a certain threshold value may be associatedwith more calm driving. For instance, a historical low number ofvehicles on a particular route segment and/or a historically low ratioof vehicles per mile, e.g., below a certain threshold value, mayindicate that the route segment has historically been a calm routesegment.

In particular, the calm/quiet route segment identifier 130 may calculatea score associated with the route segment (e.g., a “calmness score”),e.g., based at least in part upon a number of indications of calmnessand/or quietness associated with each route segment and/or a degree ofcalmness and/or quietness associated with each route segment. Forinstance, the calmness score may be calculated as a percentage out of100, as a number on a scale of 1-10, as a numerical “grade” (e.g., A, B,C, etc.), etc. Moreover, in some examples, the indications of calmnessand/or quietness associated with each route segment may include a timeassociated with each indication. For instance, a route may be very calmat particular times of day but not as calm at other times of day.

The traffic score generator 132 may be configured to analyze currenttraffic data (e.g., from the traffic database 136) associated withvarious route segments in order to calculate a traffic scorerepresenting a level of congestion along each route segment. Inparticular, the traffic score may correspond to a level of insurancerisk associated with traversing the segment. For instance, a higherscore may indicate a greater degree of congestion (e.g., a larger numberof vehicles currently traversing the route segment, a higher ratio ofvehicles per mile, etc.), and may accordingly be associated with ahigher level of insurance risk (e.g., a greater likelihood of a vehicleaccident). As discussed above with respect to the calmness score, thecongestion score may be calculated as a percentage out of 100, as anumber on a scale of 1-10, as a numerical “grade” (e.g., A, B, C, etc.),etc.

The route generator 134 may generate routes based at least in part uponuser requests for navigation directions received by the server 122 fromonboard computing devices 102. A particular user request for navigationdirections may include an indication of an origin location and adestination location, as well as an indication of whether a user hasindicated a preference for a calm route. The route generator 134 mayidentify a plurality of routes between the origin location and thedestination location using map data from the map database 138. If thereis no indication that a user has indicated a preference for a calmroute, the route generator 134 may select a route based at least in partupon factors such as which route is associated with the shortest drivingdistance, which route is associated with the shortest driving time, etc.If there is an indication that the user has indicated a preference for acalm route, the route generator 134 may select a route based at least inpart upon the indications of calmness (or “calmness score”) and thetraffic score associated with the route segments of each of theidentified plurality of routes. For example, if there is an indicationthat the user has indicated a preference for a calm route, the routegenerator 134 may select a route whose route segments have a highercalmness score and a lower traffic rather than a route associated withthe shortest driving distance or the shortest driving time. The routegenerator 134 may communicate an indication of the selected route to anonboard computing device 102 associated with the user who made therequest for navigation directions, and the navigation application 118 ofthe onboard computing device 102 may cause the route to be displayed viathe user interface 120 of the onboard computing device 102.

Moreover, the computer-readable instructions stored on the memory 128may include instructions for carrying out any of the steps of the method300 described in greater detail below with respect to FIG. 3.Furthermore, in some examples, steps described above as being performedby the processor 126 of the server 122 may be performed by the processor114 of the onboard computing device 102, or vice versa.

FIG. 2A and FIG. 2B illustrate exemplary user interface displays, inaccordance with some embodiments. For instance, as shown in FIG. 2A, auser may provide input related to a request for navigation directionsvia a user interface (e.g., user interface 120 as shown in FIG. 1),including an indication of an origin location, a destination location,and an indication of whether or not the user has a preference for a calmroute. As shown in FIG. 2B, the user interface display may shownotifications indicating upcoming maneuvers (e.g., “turn left on Highway1 in 0.5 miles”) of a selected route. In other examples (not shown), theuser interface display may include a graphic display of the route andassociated maneuvers.

Referring now to FIG. 3, a flow diagram of an exemplary method 300 forgenerating calm or quiet routes is illustrated, in accordance with someembodiments. One or more steps of the method 300 may be implemented as aset of instructions stored on a computer-readable memory and executableon one or more processors.

The method 300 may begin when a user request for navigation directionsfrom an origin location to a destination location is received (block302). In particular, a user request may include an indication of a userpreference for a calm route. For example, a user may indicate his or herpreference for a calm or quiet route using via a user interface of amobile computing device. In some examples, the user may indicate his orher preference for a calm or quiet route when requesting the navigationdirections, while in other examples, the user may indicate a generalpreference for calm or quiet routes for all requests for navigationdirections. For instance, some users may only prefer calmer or quieterroutes when they are not rushed, while other users may prefer calmer orquieter routes generally, i.e., during all or most trips.

In some examples, the indication of the user request for the calm routemay be determined based at least in part upon current heart rate dataassociated with the user. For example, current heart rate dataassociated with a user may be obtained, e.g., from a smart watch,wearable fitness tracker, etc. A higher user heart rate may be anindication of stress in the user, and may indicate that the user mightprefer a calm or quiet route. Accordingly, a calm or quiet route may beselected for a user having a high current heart rate (e.g., a heart rateabove a certain threshold heart rate), or a prompt may be provided tothe user, including an option for a user to select a calm or quietroute.

A plurality of routes between the origin location and the destinationlocation may be identified (block 304) based at least in part upon mapdata. Each route may include one or more maneuvers (e.g., turns, stops,etc.) as well as a number of route segments, i.e., portions of the routebetween each maneuver. For example, a first route between an origin(“Point A”) and a destination (“Point B”) may be to turn left from PointA onto Highway 1, drive for 2 miles, turn right on Road 2, drive for 1mile, and then turn left on Street 3 and drive for 0.5 miles to reachPoint B. The 2 miles on Highway 1, the 1 mile on Road 2, and the 0.5miles on Street 3 may each be route segments of the first route. Asecond route between Point A and Point B may be to drive straight onParkway 4 for 1 mile, then turn left on Street 3 and drive for 2.5 milesto reach point B. The 1 mile on Parkway 4, and the 2.5 miles on Street 3may each be route segments of the second route.

Historical sensor data associated with route segments of each of theplurality of routes between the origin location and the destinationlocation may be analyzed (block 306) to identify indications of calmness(and/or quietness) associated with each route segment. The historicalsensor data may include historical data received from sensors including,e.g., a heart rate sensor, a microphone fixed to a vehicle andconfigured to receive noise data from an exterior of the vehicle, anaccelerometer, an external traffic database, etc. For example, thehistorical sensor data associated with each route segment may includeheart rate data associated with operators of vehicles captured whiledriving the route segment, noise data received from exteriors ofvehicles traveling along the route segment, accelerometer dataindicative of hard breaking and acceleration events captured along theroute segment, historical traffic data along the route segment, etc. Thehistorical sensor data may include historical sensor data associatedwith the user from historical instances in which the user drove alongthe route segments, or historical sensor data associated with otherusers from historical instances in which the other users traveled alongeach route segment.

In some examples, a number of indications of calmness and/or quietnessassociated with each route segment and/or a degree of calmness and/orquietness associated with each route segment may be used to calculate ascore associated with the route segment (e.g., a “calmness score”). Forinstance, the calmness score may be calculated as a percentage out of100, as a number on a scale of 1-10, as a numerical “grade” (e.g., A, B,C, etc.), etc. Moreover, in some examples, the indications of calmnessand/or quietness associated with each route segment may include a timeassociated with each indication. For instance, a route may be very calmat particular times of day but not as calm at other times of day.

For example, identifying one or more indications of calmness associatedwith each route segment using the historical sensor data may includeidentifying one or more instances in which the microphone receives noisedata below a predetermined volume threshold and/or noise data indicativeof sounds associated with natural environments. That is, historicalnoise data indicative of sounds below a predetermined volume thresholdcaptured by microphones associated with vehicles traveling along a routesegment may indicate that the route segment has historically been a calmroute segment, which may factor into a calmness score for the routesegment. Moreover, historical noise data indicative of sounds associatedwith natural environments (e.g., waves, birds, crickets, leaves movingin the wind, etc.) captured by microphones associated with vehiclestraveling along a route segment may also indicate that the route segmenthas historically been a calm route segment, which may factor into acalmness score for the route segment. In contrast, noise data indicativeof loud sounds and/or noise data indicating a lack of sounds associatedwith natural environments captured as a vehicle travels along a routesegment may indicate that the route segment is less calm or less quiet.

Moreover, identifying one or more indications of calmness associatedwith each route segment using the historical sensor data may includeidentifying one or more instances in which the historical heart ratedata indicates an average operator heart rate below a predeterminedheart rate threshold captured as the vehicle travels along the routesegment. That is, generally speaking, calm drivers will have lower heartrates while drivers experiencing stress will have higher heart rates.Accordingly, in some examples, an average historical heart rate below apredetermined heart rate threshold for drivers traveling a particularroute segment may indicate that the route segment has historically beena calm route segment, which may factor into a calmness score for theroute segment.

As another example, identifying one or more indications of calmnessassociated with each route segment using the historical sensor data mayinclude identifying one or more instances in which the accelerometerdata indicates a number of hard breaking and/or acceleration events thatis below a certain threshold value. That is, drivers may be less calmwhen they need to brake and accelerate frequently, but may be calmerwhen they can drive steadily with fewer braking and/or accelerationevents. Accordingly, in some examples, a number of historical hardbraking and/or acceleration events associated with a route segment belowa certain threshold value may indicate that the route segment hashistorically been a calm route segment, which may factor into a calmnessscore for the route segment.

Additionally, as another example, identifying one or more indications ofcalmness associated with each route segment using the historical sensordata may include identifying one or more instances in which thehistorical traffic data indicates a level of congestion below a certainthreshold value. For instance, a historical low number of vehicles on aparticular route segment and/or a historically low ratio of vehicles permile, e.g., below a certain threshold value, may indicate that the routesegment has historically been a calm route segment, which may factorinto a calmness score for the route segment.

Furthermore, in some examples, additional or alternative historical andcurrent sensor data (and/or historical and current data from externaldatabases) associated with each of the route segments may be used toidentify indications of calmness associated with the route segments. Forexample, other historical data may be correlated with the historicalheart rate data, historical noise data, historical accelerometer dataand/or historical traffic data associated with the route segment inorder to identify other sensor data indicative of calmness. Forinstance, machine learning techniques may be used to identify othersensor data indicative of calmness, in some case specifically for aparticular user. As one example, certain historical weather data forlocations associated with route segments may be associated withincreased heart rate for certain users, or may cause increased hardbraking events for a particular user. Accordingly, for that particularuser, a reduced indication of calmness or a reduced calmness score maybe assigned to a route segment associated with certain current weatherdata.

A score may be assigned (block 308) to current traffic data associatedwith the route segments of each of the plurality of routes between theorigin location and the destination location to represent a level ofcongestion along the segment. In particular, the score may correspond toa level of insurance risk associated with traversing the segment. Forinstance, a higher score may indicate a greater degree of congestion(e.g., a larger number of vehicles currently traversing the routesegment, a higher ratio of vehicles per mile, etc.), and may accordinglybe associated with a higher level of insurance risk (e.g., a greaterlikelihood of a vehicle accident).

One of the plurality of routes between the origin location and thedestination location may be selected (block 310) based at least in partupon the indications of calmness associated with the route segments ofthe route (and/or a calmness score associated with each of the routesegments) and the congestion score assigned to the current traffic data.For instance, a route comprising route segments having higher calmnessscores and lower traffic scores may be selected instead of a routecomprising route segments having lower calmness scores and/or highertraffic scores. In some examples, the calmness score and the trafficscore for each route segment may be combined into a combined routesegment score, and the route comprising route segments having the bestcombined route segment score may be selected. In some examples,selecting the route may further include determining a time of day atwhich the user is planning to drive the route and/or an expected time ofday at which the user would travel each route segment of the route(e.g., in order to factor the fact that certain route segments may becalmer at certain times of day into the selection of the route).

The selected route from the origin location to the destination locationmay be presented (block 312) to the user, e.g., via a user interface.For example, the route may be provided as a map, as a list of maneuvers,etc.

With the foregoing, an insurance customer may opt-in to a rewards,insurance discount, or other type of program. After the insurancecustomer provides their affirmative consent, an insurance providerremote server may collect data from the customer's mobile device, smarthome controller, or other smart devices—such as with the customer'spermission or affirmative consent. The data collected may be related toinsured assets before (and/or after) an insurance-related event,including those events discussed elsewhere herein. In return, riskaverse insureds may receive discounts or insurance cost savings relatedto home, renters, personal articles, auto, and other types of insurancefrom the insurance provider.

In one aspect, data, including the types of data discussed elsewhereherein, may be collected or received by an insurance provider remoteserver, such as via direct or indirect wireless communication or datatransmission from a smart home controller, mobile device, or othercustomer computing device, after a customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance provider may then analyze the data received with thecustomer's permission to provide benefits to the customer. As a result,risk averse customers may receive insurance discounts or other insurancecost savings based at least in part upon data that reflects low riskbehavior and/or technology that mitigates or prevents risk to (i)insured assets, such as homes, personal belongings, or vehicles, and/or(ii) home or apartment occupants.

Although the foregoing text sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the disclosed may be defined by the words of the claims setforth at the end of this patent. The detailed description is to beconstrued as exemplary only and does not describe every possibleembodiment, as describing every possible embodiment would beimpractical, if not impossible. One could implement numerous alternateembodiments, using either current technology or technology developedafter the filing date of this patent, which would still fall within thescope of the claims.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (e.g., code embodiedon a non-transitory, machine-readable medium) or hardware. In hardware,the routines, etc., are tangible units capable of performing certainoperations and may be configured or arranged in a certain manner. Inexample embodiments, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware module that operates to perform certain operations asdescribed herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that may be permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC)) toperform certain operations. A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that may betemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering embodiments inwhich hardware modules are temporarily configured (e.g., programmed),each of the hardware modules need not be configured or instantiated atany one instance in time. For example, where the hardware modulescomprise a general-purpose processor configured using software, thegeneral-purpose processor may be configured as respective differenthardware modules at different times. Software may accordingly configurea processor, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules may provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multipleof such hardware modules exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the hardware modules. In embodiments in whichmultiple hardware modules are configured or instantiated at differenttimes, communications between such hardware modules may be achieved, forexample, through the storage and retrieval of information in memorystructures to which the multiple hardware modules have access. Forexample, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it may becommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented hardware modules. The performance of certain ofthe operations may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within an office environment, oras a server farm), while in other embodiments the processors may bedistributed across a number of locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment may be included in at leastone embodiment. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

As used herein, the terms “comprises,” “comprising,” “may include,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the description. Thisdescription, and the claims that follow, should be read to include oneor at least one and the singular also may include the plural unless itis obvious that it is meant otherwise.

This detailed description is to be construed as examples and does notdescribe every possible embodiment, as describing every possibleembodiment would be impractical, if not impossible. One could implementnumerous alternate embodiments, using either current technology ortechnology developed after the filing date of this application.

Although specific embodiments of the present disclosure have beendescribed, it will be understood by those of skill in the art that thereare other embodiments that are equivalent to the described embodiments.Accordingly, it is to be understood that the present disclosure is notto be limited by the specific illustrated embodiments.

What is claimed is:
 1. A computer-implemented method of generating acalm route, the method comprising: receiving, by one or more processors,a user request for navigation directions from an origin location to adestination location, wherein the user request includes an indication ofa user preference for a calm route; identifying, by the one or moreprocessors, based at least in part upon map data, a plurality of routesbetween the origin location and the destination location; receivinghistorical sensor data associated with one or more route segments ofeach route of the plurality of routes between the origin location andthe destination location from at least one of a heart rate sensor, amicrophone fixed configured to receive noise data associated with anexterior of a vehicle, an accelerometer, and an external trafficdatabase, the historical sensor data includes one of: 1) heart rate dataassociated with operators of vehicles captured while driving the routesegment, 2) noise data received from exteriors of vehicles travelingalong the route segment, 3) accelerometer data indicative of hardbraking and acceleration events captured along the route segment, and 4)historical traffic data along the route segment; identifying one or moreindications of calmness associated with each route segment of the one ormore route segments by analyzing, by the one or more processors, thehistorical sensor data; assigning, by the one or more processors, ascore to current traffic data associated with the one or more routesegments of each route of the plurality of routes between the originlocation and the destination location to represent a level of congestionalong the one or more segments, the score corresponding to a level ofinsurance risk associated with traversing the one or more segments;selecting, by the one or more processors, one route of the plurality ofroutes between the origin location and the destination location based atleast in part upon the one or more indications of calmness associatedwith the one or more route segments of the one route and the scoreassigned to the current traffic data; and presenting, by the one or moreprocessors, the selected one route from the origin location to thedestination location to a user.
 2. The method of claim 1, wherein theindication of a user preference for a calm route is an indicationdetermined based at least in part upon current heart rate dataassociated with the user.
 3. The method of claim 1, wherein identifyingone or more indications of calmness includes identifying one or moreinstances in which the microphone receives noise data that is at leastone of below a predetermined volume threshold and indicative of one ormore sounds associated with the natural environment.
 4. The method ofclaim 1, wherein identifying one or more indications of calmnessincludes identifying one or more instances in which the historical heartrate data indicates an average operator heart rate below a predeterminedheart rate threshold.
 5. The method of claim 1, wherein identifying oneor more indications of calmness includes identifying one or moreinstances in which the accelerometer data indicates a number of hardbraking and acceleration events that is below a predetermined numberthreshold.
 6. The method of claim 1, wherein identifying one or moreindications of calmness includes identifying one or more instances inwhich the historical traffic data indicates a level of congestion belowa predetermined congestion threshold.
 7. The method of claim 1, whereinanalyzing the historical sensor data includes analyzing at least part ofthe historical sensor data that is associated with one or more drivenroute segments driven by the user.
 8. A computer system for generating acalm route, the system comprising: one or more processors; and anon-transitory program memory communicatively coupled to the one or moreprocessors and storing executable instructions that, when executed bythe one or more processors, cause the computer system to: receive a userrequest for navigation directions from an origin location to adestination location, wherein the user request includes an indication ofa user preference for a calm route; identify, based at least in partupon map data, a plurality of routes between the origin location and thedestination location; receive historical sensor data associated with oneor more route segments of each route of the plurality of routes betweenthe origin location and the destination location from at least one of aheart rate sensor, a microphone fixed configured to receive noise dataassociated with an exterior of a vehicle, an accelerometer, and anexternal traffic database, the historical sensor data includes oneof: 1) heart rate data associated with operators of vehicles capturedwhile driving the route segment, 2) noise data received from exteriorsof vehicles traveling along the route segment, 3) accelerometer dataindicative of hard braking and acceleration events captured along theroute segment, and 4) historical traffic data along the route segment;identify one or more indications of calmness associated with each routesegment of the one or more route segments by analyzing the historicalsensor data; assign a score to current traffic data associated with theone or more route segments of each route of the plurality of routesbetween the origin location and the destination location to represent alevel of congestion along the one or more segments, the scorecorresponding to a level of insurance risk associated with traversingthe one or more segments; select one of the plurality of routes betweenthe origin location and the destination location based at least in partupon the one or more indications of calmness associated with the one ormore route segments of the one route and the score assigned to thecurrent traffic data; and present the selected one route from the originlocation to the destination location to a user.
 9. The computer systemof claim 8, wherein the indication of a user preference for a calm routeis an indication determined based at least in part upon current heartrate data associated with the user.
 10. The computer system of claim 8,wherein identifying one or more indications of calmness includesidentifying one or more instances in which the microphone receives noisedata that is at least one of below a predetermined volume threshold andindicative of one or more sounds associated with the naturalenvironment.
 11. The computer system of claim 8, wherein identifying oneor more indications of calmness includes identifying one or moreinstances in which the historical heart rate data indicates an averageoperator heart rate below a predetermined heart rate threshold.
 12. Thecomputer system of claim 8, wherein identifying one or more indicationsof calmness includes identifying one or more instances in which theaccelerometer data indicates a number of hard braking and accelerationevents that is below a predetermined number threshold.
 13. The computersystem of claim 8, wherein identifying one or more indications ofcalmness includes identifying one or more instances in which thehistorical traffic data indicates a level of congestion below apredetermined congestion threshold.
 14. The computer system of claim 8,wherein analyzing the historical sensor data includes analyzing at leastpart of the historical sensor data that is associated with one or moredriven route segments driven by the user.
 15. A tangible, non-transitorycomputer-readable medium storing executable instructions for generatinga calm or quiet route that, when executed by at least one processor of acomputer system, cause the computer system to: receive a user requestfor navigation directions from an origin location to a destinationlocation, wherein the user request includes an indication of a userpreference for a calm route; identify, based at least in part upon mapdata, a plurality of routes between the origin location and thedestination location; receive historical sensor data associated with oneor more route segments of each route of the plurality of routes betweenthe origin location and the destination location from at least one of aheart rate sensor, a microphone fixed configured to receive noise dataassociated with an exterior of a vehicle, an accelerometer, and anexternal traffic database, the historical sensor data includes oneof: 1) heart rate data associated with operators of vehicles capturedwhile driving the route segment, 2) noise data received from exteriorsof vehicles traveling along the route segment, 3) accelerometer dataindicative of hard braking and acceleration events captured along theroute segment, and 4) historical traffic data along the route segment;identify one or more indications of calmness associated with each routesegment of the one or more route segments by analyzing the historicalsensor data; assign a score to current traffic data associated with theone or more route segments of each route of the plurality of routesbetween the origin location and the destination location to represent alevel of congestion along the one or more segments, the scorecorresponding to a level of insurance risk associated with traversingthe one or more segments; select one of the plurality of routes betweenthe origin location and the destination location based at least in partupon the one or more indications of calmness associated with the one ormore route segments of the one route and the score assigned to thecurrent traffic data; and present the selected one route from the originlocation to the destination location to a user.
 16. The tangible,non-transitory computer-readable medium of claim 15, wherein theindication of a user preference for a calm route is an indicationdetermined based at least in part upon current heart rate dataassociated with the user.
 17. The tangible, non-transitorycomputer-readable medium of claim 15, wherein identifying one or moreindications of calmness includes identifying one or more instances inwhich the microphone receives noise data that is at least one of below apredetermined volume threshold and indicative of one or more soundsassociated with the natural environment.
 18. The tangible,non-transitory computer-readable medium of claim 15, wherein identifyingone or more indications of calmness includes identifying one or moreinstances in which the historical heart rate data indicates an averageoperator heart rate below a predetermined heart rate threshold.
 19. Thetangible, non-transitory computer-readable medium of claim 15, whereinidentifying one or more indications of calmness includes identifying oneor more instances in which the accelerometer data indicates a number ofhard braking and acceleration events that is below a predeterminednumber threshold.
 20. The tangible, non-transitory computer-readablemedium of claim 15, wherein identifying one or more indications ofcalmness includes identifying one or more instances in which thehistorical traffic data indicates a level of congestion below apredetermined congestion threshold.